The utility function method is based on multiattribute utility theory (Keeney and Raiffa 1976). The term "utility" is a generic one: It includes both the concepts of utility and value functions. The distinction between these two approaches is based on the assumption concerning the nature of the decision problem. The value function approach is applicable in the decision situations under certainty (deterministic approach). This approach assumes that the decision maker is relatively "risk neutral" or that the attributes are known with certainty. In the utility function procedure the decision maker’s attitude toward risk is incorporated into assessment of a single =-attribute utility function (Keeney 1980). The utility scores depend in part on how he or she responses to gambles (lotteries) that involve two levels of an attribute, and in part on changes that occur in his or her preferences as the attribute level changes (see trade-off analysis). Thus utility is a convenient method of including uncertainty (risk preference) into the decision-making process. The concept of a utility function is inherently probabilistic in nature.
The value and utility function approaches can be applied to a single-decision-maker situation and group decision making. The group decisions require that the individual decision maker’s value or utility functions be aggregated into a stated group value or utility function. The individual and group value/utility function approaches can be further categorized according to the nature of the information available in the decision-making process. To this end, three categories of the value/utility function methods can be distinguished: the deterministic, probabilistic, and fuzzy approaches.
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